Abstract
In this paper we propose a simple and efficient method of image classification in UAV monitoring application. Taking into consideration the color distribution two types of texture feature are considered: statistical and fractal characteristics. In the learning phase four different and efficient features were selected: energy, correlation, mean intensity and lacunarity on different color channel (R, G and B). Also, four classes of aerial images were considered (forest, buildings, grassland and flooding zone). The method of comparison, based on sub-images, average and the Minkovski distance, improves the performance of the texture-based classification. A set of 100 aerial images from UAV was tested for establishing the rate of correct classification.
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References
Pahsa, A., Kaya, P., Alat, G., Baykal, B.: Integrating navigation amp; surveillance of unmanned air vehicles into the civilian national airspaces by using ADS-B applications. In: Integrated Communications, Navigation and Surveilance Conference (ICNS 2011), pp. J7–1–J7–7 H (2011)
Dufrene Jr., W.R.: Mobile military security with concentration on unmanned aerial vehicles. In: 24th Conference in Digital Avionics Systems (DASC 2005), vol. 2, 8D.3, pp. 1–8 (2005)
Ahmad, A., Tahar, K.N., Udin, W.S., Hashim, K.A., Darwin, N., Hafis, M., Room, M., Hamid, N.F.A., Azhar, N.A.M., Azmi, S.M.: Digital aerial imagery of unmanned aerial vehicle for various applications. In: IEEE International Conference on Control System, Computing and Engineering (ICCSCE 2013), pp. 535–540 (2013)
He, Y., Wang, H., Zhang, B.: Color-based road detection in urban traffic scenes. IEEE Trans. Intell. Transp. Syst. 5, 309–318 (2004)
Zhou, H., Kong, H., Wei, L., Creighton, D., Nahavandi, S.: Efficient road detection and tracking for Unmanned Aerial Vehicle. IEEE Trans. Intell. Transp. Syst. 16, 297–309 (2015)
Lo, S.-W., Wu, J.-H., Lin, F.-P., Hsu, C.-H.: Cyber surveillance for flood disasters. Sensors 15, 2369–2387 (2015)
Lai, C.L., Yang, J.C., Chen, Y.H.: A real time video processing based surveillance system for early fire and flood detection. In: Instrumentation and Measurement Technology Conference (IMTC 2007), Warsaw, Poland, pp. 1–6 (2007)
Losson, O., Porebski, A., Vandenbroucke, N., Macaire, L.: Color texture analysis using CFA chromatic co-occurrence matrices. Computer Vision and Image Understanding 117, 747–763 (2013)
Haralick, R., Shanmugam, K., Dinstein, I.: Textural Features for Image Classification. IEEE Transactions on Systems, Man, and Cybernetics SMC-3, 610–620 (1973)
Sarker, N., Chaudhuri, B.B.: An efficient differential box-counting approach to compute fractal dimension of image. IEEE Transactions on Systems, Man, and Cybernetics 24, 115–120 (1994)
Chaudhuri, B.B., Sarker, N.: Texture segmentation using fractal dimension. IEEE Transactions on Pattern Analysis and Machine Intelligence 17, 72–77 (1995)
Barros Filho, M.N., Sobreira, F.J.A.: Accuracy of lacunarity algorithms in texture classification of high spatial resolution images from urban areas. In: XXI Congress of International Society of Photogrammetry and Remote Sensing (ISPRS 2008), Beijing, China, pp. 417–422 (2008)
Pratt, W.: Digital Image Processing: PIKS Inside, 3rd edn. John Wiley & Sons, Inc. (2001)
Popescu, D., Dobrescu, R., Angelescu, N.: Statistical texture analysis of road for moving objectives. U.P.B. Sci. Bull. Series C. 70, 75–84 (2008)
Deza, E. Deza M.: Dictionary of Distances. Elsevier (2006)
Karperien, A.: FracLac for ImageJ, available on line at: http://rsb.info.nih.gov/ij/plugins/fraclac/FLHelp/Introduction.htm
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Popescu, D., Ichim, L. (2015). Image Recognition in UAV Application Based on Texture Analysis. In: Battiato, S., Blanc-Talon, J., Gallo, G., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2015. Lecture Notes in Computer Science(), vol 9386. Springer, Cham. https://doi.org/10.1007/978-3-319-25903-1_60
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DOI: https://doi.org/10.1007/978-3-319-25903-1_60
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